docs: def predict_proba(self, X):
          """Probability estimates.
  
          The returned estimates.
  
          Parameters
          ----------
          X : array-like, shape = [n_samples, n_features]
  
          Returns
          -------
          T : array-like, shape = [n_samples, 2]
              Returns the probability of the sample for each class in the model.
          """
          y_prob = np.zeros((X.shape[0], 2))
          y_prob[:, 1] = _sigmoid(np.dot(X, self.coef_) + self.intercept_)
          y_prob[:, 0] = 1 - y_prob[:, 1]
          return y_prob